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A method for estimating and correcting the SOC value of lithium manganese oxide series battery pack

A technology for correcting lithium manganese oxide and series batteries. It is applied in the direction of measuring electricity, measuring electrical variables, and instruments. It can solve the cumulative error of the ampere-hour integration method, the internal parameters of the battery cannot be directly measured, and the open circuit voltage method cannot be estimated online. question

Active Publication Date: 2018-08-03
CHINA AUTOMOTIVE TECH & RES CENT
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Problems solved by technology

However, SOC cannot be directly measured as an internal parameter of the battery.
The estimation algorithms for SOC mainly include ampere-hour integration method, open-circuit voltage method, neural network method, and Kalman filter method. The network method is difficult to popularize due to the limitation of training data, and the Kalman filter algorithm requires high processing speed of the system

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  • A method for estimating and correcting the SOC value of lithium manganese oxide series battery pack
  • A method for estimating and correcting the SOC value of lithium manganese oxide series battery pack
  • A method for estimating and correcting the SOC value of lithium manganese oxide series battery pack

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Embodiment Construction

[0120] It should be noted that, in the case of no conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

[0121] The present invention will be described in detail below with reference to the accompanying drawings and examples.

[0122] Such as figure 1 As shown, the present invention provides a method for estimating and correcting the SOC value of lithium manganate series battery pack, comprising the following steps:

[0123] Step (1): Define the basic concept of lithium manganese oxide series battery pack in the process of charging and discharging;

[0124] Step (2): Define the basic calculation formula between the basic concepts in step (1);

[0125] Step (3): Define four suitable timings for estimating and correcting the SOC value, namely: the first suitable timing, the second suitable timing, the third suitable timing and the fourth suitable timing;

[0126] Step (4): respectively define four kinds of app...

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Abstract

The invention provides a method for estimating and correcting the SOC value of lithium manganese oxide series battery packs, redefines the SOC calculation method of single cells and battery packs, selects four different suitable timings, and uses different algorithms to correct the SOC value The remaining capacity of the single battery affected by the time-integrated cumulative error, the maximum available capacity of the single battery affected by temperature changes and aging, thereby correcting the maximum available capacity and remaining capacity of the battery pack, and realizing the correction of the single value of the SOC at a specific point in time; in addition For the real-time calculation formula of the battery pack SOC, the present invention also provides a more accurate initial value and the maximum available capacity value of the battery pack, so that the online calculated battery pack SOC is more accurate.

Description

technical field [0001] The invention belongs to the field of calculation methods for estimating and correcting the SOC value of the state of charge of an electric vehicle power battery, and in particular relates to a method for estimating and correcting the SOC value of a lithium manganese oxide series battery pack. Background technique [0002] For electric vehicles, the state of charge (SOC) of the power battery represents the remaining capacity of the battery, which acts like the fuel gauge of a traditional car fuel tank. However, SOC cannot be directly measured as an internal parameter of the battery. The estimation algorithms for SOC mainly include ampere-hour integration method, open-circuit voltage method, neural network method, and Kalman filter method. The network method is difficult to popularize due to the limitation of training data, and the Kalman filter algorithm requires high processing speed of the system. Contents of the invention [0003] In view of thi...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01R31/36
Inventor 刘蔚刘全周李占旗晏江华戎辉龚进峰赵东欣陈慧鹏
Owner CHINA AUTOMOTIVE TECH & RES CENT
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